Effect of the COVID-19 pandemic on HIV, malaria and tuberculosis indicators in Togo: an interrupted time series analysis

BMJ Glob Health. 2024 Apr 3;9(4):e013679. doi: 10.1136/bmjgh-2023-013679.

Abstract

Background: Limited data are available on the effects of the COVID-19 pandemic on health-related indicators in sub-Saharan Africa. This study aimed to estimate the effect of the COVID-19 pandemic on nine indicators of HIV, malaria and tuberculosis (TB) in Togo.

Methods: For this interrupted time series analysis, national health information system data from January 2019 to December 2021 and TB programmatic data from the first quarter of 2018 to the fourth quarter of 2022 were analysed. Nine indicators were included. We used Poisson segmented regression to estimate the immediate impact of the pandemic and per-pandemic period trends through incidence rate ratios (IRRs) with 95% CIs.

Results: Overall, there was a decrease in six of the nine indicators, ranging from 19.3% (IRR 0.807, 95% CI 0.682 to 0.955, p=0.024) for the hospitalisation of patients for malaria to 36.9% (IRR 0.631, 95% CI 0.457 to 0.871, p=0.013) for TB diagnosis by Mycobacterium tuberculosis Xpert immediately after the declaration of the COVID-19 pandemic. A comparison of the observed and predicted trends showed that the trend remained constant between the prepandemic and pandemic periods of COVID-19 for all malaria indicators. A significant downward monthly trend was observed in antiretroviral therapy initiation (IRR 0.909, 95% CI 0.892 to 0.926, p<0.001) and positive TB microscopy (IRR 0.919, 95% CI 0.880 to 0.960, p=0.002).

Conclusion: HIV, malaria and TB services were generally maintained over time in Togo despite the COVID-19 pandemic. However, given the decline in levels immediately after the onset of the pandemic, there is an urgent need to improve the preparedness of the healthcare system.

Keywords: COVID-19; HIV; Malaria; Other study design; Tuberculosis.

MeSH terms

  • COVID-19* / epidemiology
  • HIV Infections* / epidemiology
  • Humans
  • Interrupted Time Series Analysis
  • Malaria* / epidemiology
  • Pandemics
  • Togo / epidemiology
  • Tuberculosis* / epidemiology